1. Field of the Invention
This invention is in the field of medical imaging, and in particular the display of images generated from digitized data sets obtained with computerized axial tomography (CAT scanning), magnetic resonance imaging (MRI scanning), positron emission tomography (PET scanning) and ultrasound scanning.
2. Related Art
Digitized radiographic imaging is well known. CAT scanning, PET scanning, MRI scanning and in some cases ultrasound scanning all produce data sets comprised of pixels or voxels. The pixels each correspond to a designated location within the tissues being studied. Typically, the pixels are arranged in a Cartesian fashion in rows and columns and each set of rows and columns is a two dimensional slice image of the corresponding tissue within the patient being studied. A typical radiographic study may include on the order of one to four hundred slices. Each pixel also has a number assigned to it that corresponds to the responsiveness of the tissue at the location corresponding to that pixel to the radiographic modalities being used, as for example, luminance in response to an x-ray beam for CAT scanning. Most typically, each pixel is assigned a byte, and correspondingly has 256 possible luminance values.
Conventional display of images generated from such data sets are two dimensional displays of each slice. Displays are usually black, gray and white. Radiologists are then presented with a series of two dimensional images with varying shades of gray corresponding to anatomical organs, for example showing bone as black, muscle as an intermediate shade of gray and cartilage as a lighter shade of gray.
The visibility of lesions and disease processes is in such displays is variable. Diagnosis is heavily dependent upon the clinical acumen of the radiologist or clinician. Ambiguous results are often reported. Moreover, in order to appreciate lesion or disease processes in any three dimensional or volumetric sense, the clinician must view multiple slices in separate images. Image manipulation techniques currently available are often inadequate to remove obscuring features, leaving the diseased tissue or lesion occult. Current imaging techniques do not produce representations of lesions that are useful to surgeons for planning surgery. They often do not produce representations of disease processes that are useful to internists in diagnosis, selection of treatment modalities or monitoring of the progress of medical treatment. For example, two areas of particular interest wherein the prior art is inadequate include cartilage tears to be imaged for review by orthopedic surgeons and arterial plaque being treated by internists or cardiologists.
Existing imaging techniques often rely on approximation or interpolation approaches. For example, U.S. Pat. No. 6,799,066 B2 to Steines et al. uses a particular three dimensional Euclidian distance transformation to generate a contour of the surface of an organ. Others use B-spline techniques for fitting a curve to selected locations in a dataset in order to regenerate an approximated organ contour. These and other prior art techniques fail to generate a volumetric matrix of a diseased organ on which may be displayed in a useful manner for appreciating the nature and scope of a lesion or disease process. They also fail to adequately isolate the entire complex of the organ of interest and its lesion or disease process, while also actively reproducing the lesion of disease process itself. They also fail to eliminate obscuring features of the dataset. There is a need in the art for these capabilities.
There is a need in the art for a more precise and less approximate approach to displaying images based upon known digital radiographic data sets. There is a further need for isolating the organ in question from obscuring anatomy. There is a further need for generation of a volumetric matrix of the organ in question and the lesion or disease process in question. There is a further need for display of a particular organ in a manner that is useful to a treating clinician. As always, there is a continuing need for techniques responsive to manipulation and selections by an examining clinician. There is a continuing need for economy and speed. Also there is a continuing need for systems that reproduce diagnostic images in a manner that is useful and convenient for the clinicians using them.